2D Layered Materials for Memristive and Neuromorphic Applications

With many fantastic properties, memristive devices have been proposed as top candidate for next-generation memory and neuromorphic computing chips. Significant research progresses have been made in improving performance of individual memristive devices and in demonstrating functional applications based on small-scale memristive crossbar arrays. However, practical deployment of large-scale traditional metal oxides based memristive crossbar array has been challenging due to several issues, such as high-power consumption, poor device reliability, low integration density and so on. To solve these issues, new materials that possess superior properties are required. Two-dimensional (2D) layered materials exhibit many unique physical properties and show great promise in solving these challenges, further providing new opportunities to implement practical applications in neuromorphic computing. Here, recent research progress on 2D layered materials based memristive device applications is reviewed. We provide an overview of the progresses and challenges on how 2D layered materials are used to solve the issues of conventional memristive devices and to realize more complex functionalities in neuromorphic computing. Besides, we also provide an outlook on exploitation of unique properties of 2D layered materials and van der Waals heterostructures for developing new types of memristive devices and artificial neural mircrocircuits.

[1]  R. Waser,et al.  Coexistence of Grain‐Boundaries‐Assisted Bipolar and Threshold Resistive Switching in Multilayer Hexagonal Boron Nitride , 2017 .

[2]  A. Ferrari,et al.  Graphene Photonics and Optoelectroncs , 2010, CLEO 2012.

[3]  Owain Vaughan.  Working on the edge , 2019 .

[4]  F. Zhang,et al.  Electric-field induced structural transition in vertical MoTe2- and Mo1–xWxTe2-based resistive memories , 2018, Nature Materials.

[5]  Q. Vu,et al.  Two‐Terminal Multibit Optical Memory via van der Waals Heterostructure , 2018, Advanced materials.

[6]  A. Bessonov,et al.  Layered memristive and memcapacitive switches for printable electronics. , 2015, Nature materials.

[7]  Frederick T. Chen,et al.  Challenges and opportunities for HfOX based resistive random access memory , 2011, International Electron Devices Meeting.

[8]  Chuanghan Hsu,et al.  A library of atomically thin metal chalcogenides , 2018, Nature.

[9]  J. Yang,et al.  Robust memristors based on layered two-dimensional materials , 2018, 1801.00530.

[10]  H-S Philip Wong,et al.  Artificial optic-neural synapse for colored and color-mixed pattern recognition , 2018, Nature Communications.

[11]  Guangyu Zhang,et al.  Multilevel resistive switching in planar graphene/SiO2 nanogap structures. , 2012, ACS nano.

[12]  Hua Zhang,et al.  Non-volatile resistive memory devices based on solution-processed ultrathin two-dimensional nanomaterials. , 2015, Chemical Society reviews.

[13]  Michael S. Strano,et al.  Autoperforation of 2D materials for generating two-terminal memristive Janus particles , 2018, Nature Materials.

[14]  Wenjun Zhang,et al.  Layer‐by‐Layer‐Assembled Reduced Graphene Oxide/Gold Nanoparticle Hybrid Double‐Floating‐Gate Structure for Low‐Voltage Flexible Flash Memory , 2013, Advanced materials.

[15]  M. Yun,et al.  Low‐Power, Electrochemically Tunable Graphene Synapses for Neuromorphic Computing , 2018, Advanced materials.

[16]  F. Xia,et al.  Anisotropic Black Phosphorus Synaptic Device for Neuromorphic Applications , 2016, Advanced materials.

[17]  Carver A. Mead,et al.  A single-transistor silicon synapse , 1996 .

[18]  Dmitri B. Strukov,et al.  3D CMOS-memristor hybrid circuits: devices, integration, architecture, and applications , 2012, ISPD '12.

[19]  Arindam Basu,et al.  Synergistic Gating of Electro‐Iono‐Photoactive 2D Chalcogenide Neuristors: Coexistence of Hebbian and Homeostatic Synaptic Metaplasticity , 2018, Advanced materials.

[20]  Heng-Yuan Lee,et al.  An Ultrathin Forming-Free $\hbox{HfO}_{x}$ Resistance Memory With Excellent Electrical Performance , 2010, IEEE Electron Device Letters.

[21]  N. Peres,et al.  Electron tunneling through ultrathin boron nitride crystalline barriers. , 2012, Nano letters.

[22]  M. Hersam,et al.  Multi-terminal memtransistors from polycrystalline monolayer molybdenum disulfide , 2018, Nature.

[23]  Saptarshi Das,et al.  Mimicking Neurotransmitter Release in Chemical Synapses via Hysteresis Engineering in MoS2 Transistors. , 2017, ACS nano.

[24]  Jing Guo,et al.  Emulating Bilingual Synaptic Response Using a Junction-Based Artificial Synaptic Device. , 2017, ACS nano.

[25]  Farnood Merrikh-Bayat,et al.  Training and operation of an integrated neuromorphic network based on metal-oxide memristors , 2014, Nature.

[26]  N. Peres,et al.  Fine Structure Constant Defines Visual Transparency of Graphene , 2008, Science.

[27]  Deji Akinwande,et al.  Two-dimensional flexible nanoelectronics , 2014, Nature Communications.

[28]  J. Wager,et al.  Transparent Electronics , 2003, Science.

[29]  Zhengya Zhang,et al.  A fully integrated reprogrammable memristor–CMOS system for efficient multiply–accumulate operations , 2019, Nature Electronics.

[30]  J. Yang,et al.  Memristor crossbar arrays with 6-nm half-pitch and 2-nm critical dimension , 2018, Nature Nanotechnology.

[31]  Wei Yang Lu,et al.  Nanoscale memristor device as synapse in neuromorphic systems. , 2010, Nano letters.

[32]  Dmytro Pesin,et al.  Spintronics and pseudospintronics in graphene and topological insulators. , 2012, Nature materials.

[33]  L. Chua.  Memristor-The missing circuit element , 1971 .

[34]  Manuel Le Gallo,et al.  Stochastic phase-change neurons. , 2016, Nature nanotechnology.

[35]  Kinam Kim,et al.  Graphene Barristor, a Triode Device with a Gate-Controlled Schottky Barrier , 2012, Science.

[36]  Luping Shi,et al.  Truly Concomitant and Independently Expressed Short‐ and Long‐Term Plasticity in a Bi2O2Se‐Based Three‐Terminal Memristor , 2018, Advanced materials.

[37]  F. Miao,et al.  Tunable, Ultralow‐Power Switching in Memristive Devices Enabled by a Heterogeneous Graphene–Oxide Interface , 2014, Advanced materials.

[38]  Mary O'Neill,et al.  Reversible optical switching memristors with tunable STDP synaptic plasticity: a route to hierarchical control in artificial intelligent systems. , 2017, Nanoscale.

[39]  He Qian,et al.  Understanding memristive switching via in situ characterization and device modeling , 2019, Nature Communications.

[40]  Jun Du,et al.  Highly Transparent Dysprosium Oxide-Based RRAM With Multilayer Graphene Electrode for Low-Power Nonvolatile Memory Application , 2014, IEEE Transactions on Electron Devices.

[41]  Gregory S. Snider,et al.  ‘Memristive’ switches enable ‘stateful’ logic operations via material implication , 2010, Nature.

[42]  Shuangyi Zhao,et al.  Hybrid Structure of Silicon Nanocrystals and 2D WSe2 for Broadband Optoelectronic Synaptic Devices , 2018, 2018 IEEE International Electron Devices Meeting (IEDM).

[43]  X. Duan,et al.  Van der Waals heterostructures and devices , 2016 .

[44]  Yi Yang,et al.  A hardware Markov chain algorithm realized in a single device for machine learning , 2018, Nature Communications.

[45]  Candido Pirri,et al.  Memristive devices based on graphene oxide , 2015 .

[46]  Byron D. Gates.  Flexible Electronics , 2009, Science.

[47]  Peng Zhou,et al.  Two-dimensional materials for synaptic electronics and neuromorphic systems. , 2019, Science bulletin.

[48]  Shimeng Yu,et al.  Optoelectronic resistive random access memory for neuromorphic vision sensors , 2019, Nature Nanotechnology.

[49]  Wei D. Lu,et al.  Electrochemical dynamics of nanoscale metallic inclusions in dielectrics , 2014, Nature Communications.

[50]  Yuchao Yang,et al.  Observation of conducting filament growth in nanoscale resistive memories , 2012, Nature Communications.

[51]  A. Balandin.  Thermal properties of graphene and nanostructured carbon materials. , 2011, Nature materials.

[52]  Feng Yan,et al.  Two-dimensional material membranes: an emerging platform for controllable mass transport applications. , 2014, Small.

[53]  K. Terabe,et al.  Forming and switching mechanisms of a cation-migration-based oxide resistive memory , 2010, Nanotechnology.

[54]  Qi Liu,et al.  Nonpolar Nonvolatile Resistive Switching in Cu Doped $\hbox{ZrO}_{2}$ , 2008, IEEE Electron Device Letters.

[55]  Matthew T. Cole,et al.  Flexible Electronics: The Next Ubiquitous Platform , 2012, Proceedings of the IEEE.

[56]  SUPARNA DUTTASINHA,et al.  Van der Waals heterostructures , 2013, Nature.

[57]  Feng Wang,et al.  High‐temperature stability of suspended single‐layer graphene , 2010 .

[58]  Giuseppe Iannaccone,et al.  Electronics based on two-dimensional materials. , 2014, Nature nanotechnology.

[59]  Peng Lin,et al.  Fully memristive neural networks for pattern classification with unsupervised learning , 2018 .

[60]  Paul E. Hasler,et al.  Single transistor learning synapse with long term storage , 1995, Proceedings of ISCAS'95 - International Symposium on Circuits and Systems.

[61]  Jung Min Lee,et al.  Synaptic Barristor Based on Phase‐Engineered 2D Heterostructures , 2018, Advanced materials.

[62]  L.O. Chua,et al.  Memristive devices and systems , 1976, Proceedings of the IEEE.

[63]  Pritish Narayanan,et al.  Equivalent-accuracy accelerated neural-network training using analogue memory , 2018, Nature.

[64]  Eric Pop,et al.  Electronic synapses made of layered two-dimensional materials , 2018, Nature Electronics.

[65]  J. Yang,et al.  Memristive crossbar arrays for brain-inspired computing , 2019, Nature Materials.

[66]  Eric M. Vogel,et al.  Nonlinear Switching With Ultralow Reset Power in Graphene-Insulator-Graphene Forming-Free Resistive Memories , 2014, IEEE Electron Device Letters.

[67]  V. Berry.  Impermeability of graphene and its applications , 2013 .

[68]  H.-S. Philip Wong,et al.  Face classification using electronic synapses , 2017, Nature Communications.

[69]  L. Lauhon,et al.  Gate-tunable memristive phenomena mediated by grain boundaries in single-layer MoS2. , 2015, Nature nanotechnology.

[70]  F. Zeng,et al.  Recent progress in resistive random access memories: Materials, switching mechanisms, and performance , 2014 .

[71]  Andrew Pannone,et al.  Gaussian synapses for probabilistic neural networks , 2019, Nature Communications.

[72]  Jack C. Lee,et al.  Thinnest Nonvolatile Memory Based on Monolayer h‐BN , 2019, Advanced materials.

[73]  Jehoshua Bruck,et al.  Graphene-based atomic-scale switches. , 2008, Nano letters.

[74]  Sven Höfling,et al.  Electro-photo-sensitive memristor for neuromorphic and arithmetic computing , 2016 .

[75]  Michael S. Strano,et al.  Colloidal nanoelectronic state machines based on 2D materials for aerosolizable electronics , 2018, Nature Nanotechnology.

[76]  Gert Cauwenberghs,et al.  Neuromorphic Silicon Neuron Circuits , 2011, Front. Neurosci.

[77]  M. Hersam,et al.  Mixed-dimensional van der Waals heterostructures. , 2016, Nature materials.

[78]  Andre K. Geim,et al.  Electric Field Effect in Atomically Thin Carbon Films , 2004, Science.

[79]  D. Jeong,et al.  Nonvolatile Memory Materials for Neuromorphic Intelligent Machines , 2018, Advanced materials.

[80]  Damien Querlioz,et al.  Vowel recognition with four coupled spin-torque nano-oscillators , 2017, Nature.

[81]  J Joshua Yang,et al.  Memristive devices for computing. , 2013, Nature nanotechnology.

[82]  D. Stewart,et al.  The missing memristor found , 2008, Nature.

[83]  Donhee Ham,et al.  Vertical MoS2 Double-Layer Memristor with Electrochemical Metallization as an Atomic-Scale Synapse with Switching Thresholds Approaching 100 mV. , 2019, Nano letters.

[84]  Wei Yi,et al.  Biological plausibility and stochasticity in scalable VO2 active memristor neurons , 2018, Nature Communications.

[85]  Bart Swinnen,et al.  3D System Integration Technologies , 2007, ICICDT 2007.

[86]  Cong Wang,et al.  Analog–Digital Hybrid Memristive Devices for Image Pattern Recognition with Tunable Learning Accuracy and Speed , 2019, Small Methods.

[87]  I. Valov,et al.  Graphene‐Modified Interface Controls Transition from VCM to ECM Switching Modes in Ta/TaOx Based Memristive Devices , 2015, Advanced materials.

[88]  Jing Guo,et al.  Atomically Thin Femtojoule Memristive Device , 2017, Advanced materials.

[89]  Enge Wang,et al.  Epitaxial growth of a 100-square-centimetre single-crystal hexagonal boron nitride monolayer on copper , 2019, Nature.

[90]  P. Narayanan,et al.  Access devices for 3D crosspoint memorya) , 2014 .

[91]  He Tian,et al.  In Situ Tuning of Switching Window in a Gate‐Controlled Bilayer Graphene‐Electrode Resistive Memory Device , 2015, Advanced materials.

[92]  Rong Zhang,et al.  A light-stimulated synaptic device based on graphene hybrid phototransistor , 2017 .

[93]  Qingyun Wu,et al.  Prospects of spintronics based on 2D materials , 2017 .

[94]  Eric Pop,et al.  3D Monolithic Stacked 1T1R cells using Monolayer MoS2 FET and hBN RRAM Fabricated at Low (150°C) Temperature , 2018, 2018 IEEE International Electron Devices Meeting (IEDM).

[95]  Yi Yang,et al.  Graphene Dynamic Synapse with Modulatable Plasticity. , 2015, Nano letters.

[96]  Shimeng Yu,et al.  Metal–Oxide RRAM , 2012, Proceedings of the IEEE.

[97]  N. Koratkar,et al.  Effect of defects on the intrinsic strength and stiffness of graphene , 2013, Nature Communications.

[98]  R. Douglas,et al.  A silicon neuron , 1991, Nature.

[99]  H.-S. Philip Wong,et al.  Phase Change Memory , 2010, Proceedings of the IEEE.

[100]  Yi Yang,et al.  A novel artificial synapse with dual modes using bilayer graphene as the bottom electrode. , 2017, Nanoscale.

[101]  T. Taniguchi,et al.  Evidence for Defect-Mediated Tunneling in Hexagonal Boron Nitride-Based Junctions. , 2015, Nano letters.

[102]  Peng Zhou,et al.  2D Atomic Crystals: A Promising Solution for Next‐Generation Data Storage , 2019, Advanced Electronic Materials.

[103]  M. Pickett,et al.  A scalable neuristor built with Mott memristors. , 2013, Nature materials.

[104]  Bin Zhang,et al.  Graphene and its derivatives: switching ON and OFF. , 2012, Chemical Society reviews.

[105]  Rong Zhao,et al.  Synaptic Computation Enabled by Joule Heating of Single-Layered Semiconductors for Sound Localization. , 2018, Nano letters.

[106]  Paul E. Hasler,et al.  A high-resolution non-volatile analog memory cell , 1995, Proceedings of ISCAS'95 - International Symposium on Circuits and Systems.

[107]  Kyeongjae Cho,et al.  Charge Mediated Reversible Metal-Insulator Transition in Monolayer MoTe2 and WxMo1-xTe2 Alloy. , 2016, ACS nano.

[108]  Hong-Yu Chen,et al.  Metal oxide-resistive memory using graphene-edge electrodes , 2015, Nature Communications.

[109]  Barry P Rand,et al.  Extremely Low Operating Current Resistive Memory Based on Exfoliated 2D Perovskite Single Crystals for Neuromorphic Computing. , 2017, ACS nano.

[110]  Christopher J. Brennan,et al.  A review on mechanics and mechanical properties of 2D materials—Graphene and beyond , 2016, 1611.01555.

[111]  Qing Wan,et al.  2D MoS2 Neuromorphic Devices for Brain-Like Computational Systems. , 2017, Small.

[112]  Feng Miao,et al.  A selector device based on graphene–oxide heterostructures for memristor crossbar applications , 2015 .

[113]  R. Ruoff,et al.  Graphene and Graphene Oxide: Synthesis, Properties, and Applications , 2010, Advanced materials.

[114]  Wei Zhang,et al.  Single-element glass to record data , 2018, Nature Materials.

[115]  E. Reed,et al.  Structural phase transition in monolayer MoTe2 driven by electrostatic doping , 2017, Nature.

[116]  Wei Lu,et al.  The future of electronics based on memristive systems , 2018, Nature Electronics.

[117]  Yong Ju Park,et al.  Graphene‐Based Flexible and Stretchable Electronics , 2016, Advanced materials.

[118]  Henry Markram,et al.  Synaptic pathways in neural microcircuits , 2005, Trends in Neurosciences.

[119]  Shibing Long,et al.  Graphene and Related Materials for Resistive Random Access Memories , 2017 .

[120]  Jing Kong,et al.  Synthesis of large-area multilayer hexagonal boron nitride sheets on iron substrates and its use in resistive switching devices , 2018, 2D Materials.

[121]  X. Miao,et al.  Ultrafast Synaptic Events in a Chalcogenide Memristor , 2013, Scientific Reports.

[122]  Ming Liu,et al.  Time‐Tailoring van der Waals Heterostructures for Human Memory System Programming , 2019, Advanced science.

[123]  Changsheng Xie,et al.  Scalable and ultrafast epitaxial growth of single-crystal graphene wafers for electrically tunable liquid-crystal microlens arrays. , 2019, Science bulletin.

[124]  H. Ohno,et al.  Artificial Neuron and Synapse Realized in an Antiferromagnet/Ferromagnet Heterostructure Using Dynamics of Spin–Orbit Torque Switching , 2019, Advanced materials.

[125]  Armantas Melianas,et al.  Parallel programming of an ionic floating-gate memory array for scalable neuromorphic computing , 2019, Science.

[126]  Mahadev Satyanarayanan,et al.  How we created edge computing , 2019, Nature Electronics.

[127]  J. Kysar,et al.  Measurement of the Elastic Properties and Intrinsic Strength of Monolayer Graphene , 2008, Science.

[128]  Yao Li,et al.  Structural semiconductor-to-semimetal phase transition in two-dimensional materials induced by electrostatic gating , 2016, Nature Communications.

[129]  J. Yang,et al.  Emerging Memory Devices for Neuromorphic Computing , 2019, Advanced Materials Technologies.

[130]  Xin Huang,et al.  Artificial Synapses Based on Multiterminal Memtransistors for Neuromorphic Application , 2019, Advanced Functional Materials.

[131]  Heung Cho Ko,et al.  Highly flexible and transparent multilayer MoS2 transistors with graphene electrodes. , 2013, Small.

[132]  Yongli He,et al.  Coplanar Multigate MoS2 Electric-Double-Layer Transistors for Neuromorphic Visual Recognition. , 2018, ACS applied materials & interfaces.

[133]  Qing Wan,et al.  Proton‐Conducting Graphene Oxide‐Coupled Neuron Transistors for Brain‐Inspired Cognitive Systems , 2015, Advanced materials.

[134]  Qing Wan,et al.  Artificial synapse network on inorganic proton conductor for neuromorphic systems. , 2014, Nature communications.

[135]  Yu Huang,et al.  Van der Waals integration before and beyond two-dimensional materials , 2019, Nature.

[136]  Wei Han,et al.  Graphene spintronics. , 2014, Nature nanotechnology.

[137]  Damien Querlioz,et al.  Neuromorphic computing with nanoscale spintronic oscillators , 2017, Nature.

[138]  Young Sun,et al.  All‐Solid‐State Synaptic Transistor with Ultralow Conductance for Neuromorphic Computing , 2018, Advanced Functional Materials.

[139]  Qi Liu,et al.  Eliminating Negative‐SET Behavior by Suppressing Nanofilament Overgrowth in Cation‐Based Memory , 2016, Advanced materials.

[140]  R. Dittmann,et al.  Redox‐Based Resistive Switching Memories – Nanoionic Mechanisms, Prospects, and Challenges , 2009, Advanced materials.

[141]  Shimeng Yu,et al.  Monitoring oxygen movement by Raman spectroscopy of resistive random access memory with a graphene-inserted electrode. , 2013, Nano letters.

[142]  M. Kozicki,et al.  Bipolar and Unipolar Resistive Switching in Cu-Doped $ \hbox{SiO}_{2}$ , 2007, IEEE Transactions on Electron Devices.

[143]  Hui Long,et al.  Mass transport mechanism of cu species at the metal/dielectric interfaces with a graphene barrier. , 2014, ACS nano.

[144]  K. Novoselov,et al.  2D materials and van der Waals heterostructures , 2016, Science.

[145]  Myungsoo Kim,et al.  Atomristor: Nonvolatile Resistance Switching in Atomic Sheets of Transition Metal Dichalcogenides. , 2018, Nano letters.

[146]  Subhasish Mitra,et al.  Three-dimensional integration of nanotechnologies for computing and data storage on a single chip , 2017, Nature.

[147]  S. Balatti,et al.  Resistive Switching by Voltage-Driven Ion Migration in Bipolar RRAM—Part II: Modeling , 2012, IEEE Transactions on Electron Devices.

[148]  Xiang Zhang,et al.  Two-dimensional magnetic crystals and emergent heterostructure devices , 2019, Science.

[149]  Weiguang Xie,et al.  Graphene Based Non‐Volatile Memory Devices , 2014, Advanced materials.

[150]  N. Peres,et al.  Electron tunneling through ultrathin boron nitride crystalline barriers. , 2012, Nano letters.

[151]  Shinhyun Choi,et al.  SiGe epitaxial memory for neuromorphic computing with reproducible high performance based on engineered dislocations , 2018, Nature Materials.

[152]  Hua Zhang,et al.  Two-dimensional semiconductors for transistors , 2016 .

[153]  Wei D. Lu,et al.  Ionic modulation and ionic coupling effects in MoS2 devices for neuromorphic computing , 2018, Nature Materials.

[154]  Weiwei Xia,et al.  Memristor Crossbars with 4.5 Terabits-per-Inch-Square Density and Two Nanometer Dimension , 2018, ArXiv.

[155]  H.-S. Philip Wong,et al.  In-memory computing with resistive switching devices , 2018, Nature Electronics.

[156]  Qi Liu,et al.  Breaking the Current‐Retention Dilemma in Cation‐Based Resistive Switching Devices Utilizing Graphene with Controlled Defects , 2018, Advanced materials.

[157]  Chen Pan,et al.  S‐Type Negative Differential Resistance in Semiconducting Transition‐Metal Dichalcogenides , 2019, Advanced Electronic Materials.

[158]  Wei Zhang,et al.  Reducing the stochasticity of crystal nucleation to enable subnanosecond memory writing , 2017, Science.

[159]  Govind,et al.  Electronic interaction and bipolar resistive switching in copper oxide-multilayer graphene hybrid interface: Graphene as an oxygen ion storage and blocking layer , 2011 .

[160]  Juerg Leuthold,et al.  Optical memristive switches , 2017, Journal of Electroceramics.

[161]  Qing Hua Wang,et al.  Electronics and optoelectronics of two-dimensional transition metal dichalcogenides. , 2012, Nature nanotechnology.

[162]  T. Hasegawa,et al.  Short-term plasticity and long-term potentiation mimicked in single inorganic synapses. , 2011, Nature materials.

[163]  Young Sun,et al.  A Synaptic Transistor based on Quasi‐2D Molybdenum Oxide , 2017, Advanced materials.

[164]  Bin Wu,et al.  MoS2 Memristors Exhibiting Variable Switching Characteristics toward Biorealistic Synaptic Emulation. , 2018, ACS nano.

[165]  D. Akinwande,et al.  Graphene and two-dimensional materials for silicon technology , 2019, Nature.

[166]  J. Tour,et al.  Highly transparent nonvolatile resistive memory devices from silicon oxide and graphene , 2012, Nature Communications.

[167]  Jiaming Zhang,et al.  Analogue signal and image processing with large memristor crossbars , 2017, Nature Electronics.

[168]  Jingzhao Zhang,et al.  Gate-tunable room-temperature ferromagnetism in two-dimensional Fe3GeTe2 , 2018, Nature.

[169]  Yan Wang,et al.  Infrared‐Sensitive Memory Based on Direct‐Grown MoS2–Upconversion‐Nanoparticle Heterostructure , 2018, Advanced materials.

[170]  Bai-Sun Kong,et al.  Self-selective van der Waals heterostructures for large scale memory array , 2019, Nature Communications.

[171]  R. Dittmann,et al.  Quantifying redox-induced Schottky barrier variations in memristive devices via in operando spectromicroscopy with graphene electrodes , 2016, Nature Communications.

[172]  David-Wei Zhang,et al.  A MoS2/PTCDA Hybrid Heterojunction Synapse with Efficient Photoelectric Dual Modulation and Versatility , 2018, Advanced materials.

[173]  P. Ajayan,et al.  Room temperature 2D memristive transistor with optical short-term plasticity , 2017, 2017 IEEE International Electron Devices Meeting (IEDM).

[174]  B. Cho,et al.  Organic Resistive Memory Devices: Performance Enhancement, Integration, and Advanced Architectures , 2011 .

[175]  Yuchao Yang,et al.  Oxide Resistive Memory with Functionalized Graphene as Built‐in Selector Element , 2014, Advanced materials.

[176]  Fengnian Xia,et al.  Black phosphorus and its isoelectronic materials , 2019, Nature Reviews Physics.

[177]  J. Yang,et al.  Memristors with diffusive dynamics as synaptic emulators for neuromorphic computing. , 2017, Nature materials.

[178]  Peng Lin,et al.  Reinforcement learning with analogue memristor arrays , 2019, Nature Electronics.

[179]  Nagarajan Raghavan,et al.  Recommended Methods to Study Resistive Switching Devices , 2018, Advanced Electronic Materials.

[180]  Yuchao Yang,et al.  Ion Gated Synaptic Transistors Based on 2D van der Waals Crystals with Tunable Diffusive Dynamics , 2018, Advanced materials.